medical response
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Author(s):  
Susan Miller Briggs ◽  
Dennis T. Cherian ◽  
Alfonso C. Rosales
Keyword(s):  

2021 ◽  
pp. 003335492110587
Author(s):  
Andrew D. Redd ◽  
Lauren S. Peetluk ◽  
Brooke A. Jarrett ◽  
Colleen Hanrahan ◽  
Sheree Schwartz ◽  
...  

The public health crisis created by the COVID-19 pandemic has spurred a deluge of scientific research aimed at informing the public health and medical response to the pandemic. However, early in the pandemic, those working in frontline public health and clinical care had insufficient time to parse the rapidly evolving evidence and use it for decision-making. Academics in public health and medicine were well-placed to translate the evidence for use by frontline clinicians and public health practitioners. The Novel Coronavirus Research Compendium (NCRC), a group of >60 faculty and trainees across the United States, formed in March 2020 with the goal to quickly triage and review the large volume of preprints and peer-reviewed publications on SARS-CoV-2 and COVID-19 and summarize the most important, novel evidence to inform pandemic response. From April 6 through December 31, 2020, NCRC teams screened 54 192 peer-reviewed articles and preprints, of which 527 were selected for review and uploaded to the NCRC website for public consumption. Most articles were peer-reviewed publications (n = 395, 75.0%), published in 102 journals; 25.1% (n = 132) of articles reviewed were preprints. The NCRC is a successful model of how academics translate scientific knowledge for practitioners and help build capacity for this work among students. This approach could be used for health problems beyond COVID-19, but the effort is resource intensive and may not be sustainable in the long term.


Author(s):  
Howard Backer ◽  
David Duncan ◽  
Kate Christensen ◽  
Asha Devereaux ◽  
Brett Rosen ◽  
...  

Abstract Wildfires have become a regular seasonal disaster across the Western region of the United States. Wildfires require a multifaceted disaster response. In addition to fire suppression, there are public health and medical needs for responders and the general population in the path of the fire, as well as a much larger population impacted by smoke. This paper describes key aspects of the health and medical response to wildfires in California, including facility evacuation and shelter medical support, with emphasis on the organization, coordination, and management of medical teams deployed to fire incident base camps. This provides 1 model of medical support and references resources to help other jurisdictions that must respond to the rising incidence of large wildland fires.


Author(s):  
You Yeon Choi ◽  
Seung Yeol Yoo ◽  
Mihyun Yang ◽  
Ki Moon Seong

Radiation emergency medicine (REM) systems are operated around the world to provide specialized care for injured individuals who require immediate medical attention in accidents. This manuscript describes the current status of REM safety regulation in Korea and summarizes an assessment of the effects of this regulation. Responding to the requests of people for stronger safety regulations related to radiation exposure, a unique REM safety regulation for nuclear licensees, which is enforceable by laws, has been established and implemented. It is not found in other countries. It can provide a good example in practice for sustainable REM management including document reviews on medical response procedures and inspections of equipment and facilities. REM preparedness of nuclear or radiologic facilities has been improved with systematic implementation of processes contained in the regulation. In particular, the medical care system of licensees has become firmly coordinated in the REM network at the national level, which has enhanced their abilities by providing adequate medical personnel and facilities. This legal regulation service has contributed to preparing the actual medical emergency response for unexpected accidents and should ultimately secure the occupational safety for workers in radiation facilities.


2021 ◽  
Vol 27 (4) ◽  
pp. 4125-4127
Author(s):  
Elena Valkanova ◽  
◽  
Rostislav Kostadinov ◽  

Introduction: Disaster medicine is a novel but rapidly evolving medical specialty. It aims for evidence based practices as they are essential for contemporary medicine. Every calamity provides input for development. Researchers in the field study these events for the purpose of amending theory and practice to reflect new challenges. The better the understanding of the shortfalls reported is, the greater will the worth for disaster medical response to the upcoming events be. Purpose: The objective of the study is to demonstrate the connection between disasters and commencement and evolution in disaster medicine education and to highlight the significance of lessons learned for practice improvement. Materials and methods: By means of the descriptive method, lessons learned from disaster medical support to some of the most significant catastrophic events in recent years are presented. Comparative and deductive analyses are performed in order to assess the influence of disasters on the evolution of disaster medical support education and training. Results: Analysis of the most consequential disasters proves that the affected countries have implemented disaster medical support planning, organization, and management changes. These changes in policy and practice lead to amendments and advances in disaster medical tuition. Conclusion: As a conclusion, disaster medicine education reliance on the best practices approved throughout the disaster relief operations is noted. Every gained experience and lesson learned have to be implemented into the lectures and seminars, thus transforming real life achievements into knowledge and wisdom.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nur Budi Mulyono ◽  
Noorhan Firdaus Pambudi ◽  
Lukni Burhanuddin Ahmad ◽  
Akbar Adhiutama

PurposeThe lack of studies about the response time of emergency medical service during the coronavirus disease 2019 (COVID-19) pandemic in a dense city of a developing country has triggered this study to explore the factors contributing to a high response time of ambulance service to reach patients in need. An evaluation of contributing factors to the response time is necessary to guide decision-makers in keeping a high service level of emergency medical service.Design/methodology/approachThis research employed an agent-based modeling approach with input parameters from interviews with emergency medical service staff in Bandung city, Indonesia. The agent-based model is established to evaluate the relevant contribution of the factors to response time reduction using several scenarios.FindingsAccording to agent-based simulation, four factors contribute to the response time: the process of preparing crew and ambulance during the pandemic, coverage area, traffic density and crew responsiveness. Among these factors, the preparation process during the pandemic and coverage area significantly contributed to the response time, while the traffic density and crew responsiveness were less significant. The preparation process is closely related to the safety procedure in handling patients during the COVID-19 pandemic and normal time. The recommended coverage area for maintaining a low response time is 5 km, equivalent to six local subdistricts.Research limitations/implicationsThis study has explored the factors contributing to emergency medical response time. The insignificant contribution of the traffic density showed that citizens, in general, have high awareness and compliance to traffic priority regulation, so crew responsiveness in handling ambulances is an irrelevant factor. This study might have different contributing factors for less dense population areas and focuses on public emergency medical services provided by the local government.Practical implicationsThe local government must provide additional funding to cover additional investment for ambulance, crew and administration for the new emergency service deployment point. Exercising an efficient process in ambulance and crew preparation is mandatory for each emergency deployment point.Originality/valueThis study evaluates the contributing factors of emergency medical response time in the pandemic and normal situation by qualitative analysis and agent-based simulation. The performance comparison in terms of medical response time before and after COVID-19 through agent-based simulation is valuable for decision-makers to reduce the impact of COVID-19.


2021 ◽  
Vol 23 (11) ◽  
pp. 429-438
Author(s):  
Yashi Sharma ◽  
◽  
Dr. Brajesh Kumar Singh ◽  

Depression is seen as an emerging mental challenge in the lives of various people. Nowadays it is also becoming one of the major reasons for mental disability across the world. Depression has manifested itself as a silent killer and according to statistics it has affected more than 300 million people in United States of America majorly affecting individuals in the age group of 15 to 44 yrs. According to a study by World Health Organization, the effects of depression have been dangerous in life, it is seen causing threatening diseases like cancer, diabetic issues or even heart disease. However, the problem that mainly is associated with the disease of depression is that it is not treated as a disease. Where the common understanding of the word “Disease” is any medical ailment that require doctor’s attention or quick medical response, depression on the other hand, even after qualifying as a disease is hidden in societal barriers to appear for a proper treatment. People whose lifestyle pattern has been intruded by depression either do not avail proper medical attention or are too shy to appear in the masses for proper attention on their physical as well as condition. Our motivation here is to investigate through the phenomenon of depression and predict whether an individual is having symptoms of depression by accessing his/her voice sample. In order to establish a link between depression and voice features, we obtain a large data set and then train a model accordingly by applying machine learning methods on it. This model when given a voice sample can now predict, whether a particular subject is depressed or not, to a nearby accurate measure.


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